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A Change Point Problem in the Regression Model When the Errors are Correlated
Cho, Sinsup,Cho, Kwan Ho,Song, Moon Sup The Korean Society for Quality Management 1988 품질경영학회지 Vol.16 No.2
Testing procedures for a detection of change point in the regression model with correlated errors are discussed. A Bayesian approach is adopted and applied to a regression model with errors following an AR(1) model.
Long Memory Characteristics in the Korean Stock Market Volatility
Cho, Sinsup,Choe, Hyuk,Park, Joon Y 한국통계학회 2002 Communications for statistical applications and me Vol.9 No.3
For the estimation and test of long memory feature in volatilities of stock indices and individual companies semiparametric approach, Geweke and Porter-Hudak (1983), is employed. Empirical study supports the strong evidence of volatility persistence in Korean stock market. Most of indices and individual companies have the feature of long term dependence of volatility. Hence the short memory models are unable to explain the volatilities in Korean stock market.
Comparison of Linear Trend on Control Charts
Cho, Sinsup,Lee, Jeong Hyeong 한국품질경영학회 2002 The Asian Journal on Quality Vol.3 No.1
On control chart, one may use the regression, cusum and exponential smoothing methods to detect any change in the trend of the process. When the data is observed with equally spaced time interval we show how to obtain the estimates of the trend for each method. Three different estimation methods are compared through simulation in terms of efficiency, MSE, MAPE and MAD. It is observed that OLS performs well in general. Cusum is found to be most sensitive to the outliers even though it is simple to compute. We recommend the use of the EWMA method when the error distribution is heavy tailed.
조신섭,Cho, Sinsup 한국통계학회 2021 응용통계연구 Vol.34 No.4
공식통계 및 사회조사통계 정보들이 언론에 보도되는 과정에서 발생하는 여러가지 문제점을 사례중심으로 살펴보고 이의 해결방안에 대해 알아보았다. In this paper we investigate the problems revealed when the statistics are published in the press.
Bootstrapping Log Periodogram Regression
Nam, Gilnam,Cho, Sinsup,Yeo, In-Kwon The Korean Statistical Society 2003 Communications for statistical applications and me Vol.10 No.3
In this paper, we consider a modified bootstrap scheme for inference of the GPH estimator and establish the sup-norm consistency of the proposed bootstrapping.
Model for the Spatial Time Series Data
Lim, Seongsik,Cho, Sinsup,Lee, Changsoo The Korean Society for Quality Management 1996 품질경영학회지 Vol.24 No.1
We propose a model which is useful for the analysis of the spatial time series data. The proposed model utilized the linear dependences across the spatial units as well as over time. Three stage model fitting procedures are suggested and the real data is analyzed.
Analysis of Composit Index Using the Time Series Model
Jeong Hyeong Lee,Sinsup Cho 한국자료분석학회 1999 Journal of the Korean Data Analysis Society Vol.1 No.1
The leading index gives useful information for the prediction of an economic event and the coincident index provides a summary of the state of actual economic activity. It has been observed that there exist regular and short time lags, usually 3 or 4 months, between the leading index and the coincident index. In this paper, therefore, we evaluate the index of leading indicators as a tool for prediction. From this standpoint, the relationships between the leading indicators and the coincident index are analyzed by both the regression model and the time series model (transfer function model). And the predictive performances of each model are compared.
Problems of Special Causes in Feedback Adjustment
Lee, Jae June,Cho, Sinsup 한국품질경영학회 2004 품질경영학회지 Vol.32 No.2
Process adjustment is a complimentary tool to process monitoring in process control. Process adjustment directs on maintaining a process output close to a target value by manipulating another controllable variable, by which significant process improvement can be achieved. Therefore, this approach can be applied to the 'Improve' stage of Six Sigma strategy. Though the optimal control rule minimizes process variability in general, it may not properly function when special causes occur in underlying process, resulting in off-target bias and increased variability in the adjusted output process, possibly for long periods. In this paper, we consider a responsive feedback control system and the minimum mean square error control rule. The bias in the adjusted output process is investigated in a general framework, especially focussing on stationary underlying process and the special cause of level shift type. Illustrative examples are employed to illustrate the issues discussed.